A Decision Tree is a visual and intuitive machine learning method that makes decisions by asking questions about the data. It works like a flowchart, starting with a question at the top and branching out based on answers. These questions are not just yes/no, but can also be comparisons, like "Is the age greater than 18?" or "Is the temperature below 30°C?" Each split is chosen using a quantitative measure, such as information gain or Gini impurity, to find the best threshold for separating the data.
You will form teams of two and use the training data to develop criteria for distinguishing biting from non-biting monkeys. These must be clearly noted so that they can be appli...
